Center for Lower Extremity Ambulatory Research, Scholl College of Podiatric Medicine, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA.
Gerontology. 2012;58(5):463-71. doi: 10.1159/000338095. Epub 2012 May 10.
Individuals with diabetes have a higher risk of falls and fall-related injuries. People with diabetes often develop peripheral neuropathy (DPN) as well as nerve damage throughout the body. In particular, reduced lower extremity proprioception due to DPN may cause a misjudgment of foot position and thus increase the risk of fall.
An innovative virtual obstacle-crossing paradigm using wearable sensors was developed in an attempt to assess lower extremity position perception damage due to DPN.
67 participants (age 55.4 ± 8.9, BMI 28.1 ± 5.8) including diabetics with and without DPN as well as aged-matched healthy controls were recruited. Severity of neuropathy was quantified using a vibratory perception threshold (VPT) test. The ability of perception of lower extremity was quantified by measuring obstacle-crossing success rate (OCSR), toe-obstacle clearance (TOC), and reaction time (T(R)) while crossing a series of virtual obstacles with heights at 10% and 20% of the subject's leg length.
No significant difference was found between groups for age and BMI. The data revealed that DPN subjects had a significantly lower OCSR compared to diabetics with no neuropathy and controls at an obstacle size of 10% of leg length (p < 0.05). DPN subjects also demonstrated longer T(R) compared to other groups and for both obstacle sizes. In addition, TOC was reduced in neuropathy groups. Interestingly, a significant correlation between T(R) and VPT (r = 0.5, p < 10(-3)) was observed indicating a delay in reaction with increasing neuropathy severity. The delay becomes more pronounced by increasing the size of the obstacle. Using a regression model suggests that the change in T(R) between obstacle sizes of 10% and 20% of leg length is the most sensitive predictor for neuropathy severity with an odds ratio of 2.70 (p = 0.02).
The findings demonstrate proof of a concept of virtual-reality application as a promising method for objective assessment of neuropathy severity, however a further study is warranted to establish a stronger relationship between the measured parameters and neuropathy.
糖尿病患者有更高的跌倒和与跌倒相关的受伤风险。糖尿病患者通常会出现周围神经病变(DPN)以及全身神经损伤。特别是,DPN 导致的下肢本体感觉减退可能会导致对足部位置的误判,从而增加跌倒的风险。
开发了一种使用可穿戴传感器的创新虚拟过障碍范式,试图评估 DPN 引起的下肢位置感知损伤。
招募了 67 名参与者(年龄 55.4 ± 8.9,BMI 28.1 ± 5.8),包括患有和不患有 DPN 的糖尿病患者以及年龄匹配的健康对照组。使用振动感觉阈值(VPT)测试来量化神经病变的严重程度。通过测量过一系列虚拟障碍物的成功率(OCSR)、脚趾-障碍物间隙(TOC)和反应时间(T(R))来量化对下肢的感知能力,障碍物的高度分别为腿部长度的 10%和 20%。
组间年龄和 BMI 无显著差异。数据显示,在障碍物高度为腿部长度的 10%时,患有 DPN 的受试者的 OCSR 明显低于无周围神经病变的糖尿病患者和对照组(p < 0.05)。与其他组相比,DPN 受试者的 T(R)也更长,并且对于两个障碍物大小都是如此。此外,神经病变组的 TOC 减少。有趣的是,观察到 T(R)与 VPT 之间存在显著相关性(r = 0.5,p < 10(-3)),表明随着神经病变严重程度的增加,反应时间延迟。随着障碍物尺寸的增加,延迟变得更加明显。使用回归模型表明,在腿部长度的 10%和 20%之间的障碍物尺寸变化是预测神经病变严重程度的最敏感指标,优势比为 2.70(p = 0.02)。
研究结果证明了虚拟现实应用作为一种有前途的神经病变严重程度客观评估方法的概念验证,然而,需要进一步的研究来建立所测参数与神经病变之间的更强关系。